Experimental Investigation of an Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller for Buck DC/DC Converters

This study proposes a way of designing reliable voltage controller for buck DC/DC converter in which the terminal attractor approach is combined with an enhanced reaching law-based Fast Terminal Synergetic Controller (FTSC). The proposed scheme will overcome chattering phenomena constraint existing Sliding Mode Controllers (SMCs) and issue related to indefinite time convergence traditional (SCs). In this approach, FTSC algorithm ensure proper tracking while law guarantee finite-time convergence. A Fuzzy Neural Network (FNN) structure exploited here approximate unknown nonlinear dynamics due changes input loads. weights are adjusted according adaptive real-time respond system uncertainties, enhancing increasing system’s robustness. applicability controller, i.e., Adaptive Fuzzy-Neural (AFN-FTSC), evaluated through comprehensive analyses platforms, along rigorous comparative studies FTSC. dSPACE ds1103 platform used implementation scheme. All results confirm fast reference capability low overshoots robustness against disturbances comparing